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library("nycflights13")
library("tidyverse")

nycflights13::flights

View(flights)
?flights

int stands for integers.

dbl stands for doubles, or real numbers.

chr stands for character vectors, or strings.

dttm stands for date-times (a date + a time).

jan1 <- filter(flights, month == 1, day == 1)

filter(flights, month == 11 | month == 12)

If you want to determine if a value is missing, use is.na()

filter() only includes rows where the condition is TRUE; it excludes both FALSE and NA values. If you want to preserve missing values, ask for them explicitly
- to ask explicitly, use comment notation to do this in parenthesis after command

Exercises 5.2:

filter(flights, arr_delay >= 120) #10,200 flights

filter(flights, dest == "IAH" | dest == "HOU") #9,313 flights

airlines 

filter(flights, carrier == "DL" | carrier == "AA" | carrier == "UA") #139,504 flights

filter(flights, month >= 7, month <= 9) #86,326 flights

  #with between fcn could do as 
  filter(flights, between(month, 7, 9))

summary(flights$dep_time)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
      1     907    1401    1349    1744    2400    8255 

filter(flights, dep_time <= 600 | dep_time == 2400) #8,255 flights

filter(flights, is.na(dep_time))

5.3 arrange() works similarly to filter() except that instead of selecting rows, it changes their order

arrange(flights, year, month, day)

Use desc() to re-order by a column in descending order and missing values are always sorted at the end

5.3 Exersices:

arrange(flights, is.na(desc(dep_delay)))

arrange(flights, desc(is.na(dep_time)), dep_time)

arrange(flights, desc(dep_delay)) #longest to shortest

arrange(flights, dep_delay) #shortest to longest

arrange(flights, desc(distance)) #4983 miles

arrange(flights, distance) #17 miles

5.4 select() allows you to rapidly zoom in on a useful subset using operations based on the names of the variables

b/c some data sets have hundreds or thousands of variables and not all are necessary for analysis–use select to just look at and work with the ones that are

starts_with(“abc”): matches names that begin with “abc”. ends_with(“xyz”): matches names that end with “xyz”. contains(“ijk”): matches names that contain “ijk”.

5.4 Exercises

select(flights, "dep_time", "dep_delay", "arr_time", "arr_delay")

select(flights, dep_time, dep_delay, arr_time, arr_delay)

select(flights, 4, 6, 7, 9) #this one uses column numbers of the variables

select(flights, starts_with("dep_"), starts_with("arr_"))

5.5 useful to add new columns that are functions of existing columns , for this we can use mutate()

flights_sml <- select(flights, 
  year:day, 
  ends_with("delay"), 
  distance, 
  air_time
)
mutate(flights_sml,
  gain = dep_delay - arr_delay,
  speed = distance / air_time * 60
)

5.5 Exercises

arr_time

Error: object 'arr_time' not found

5.6 summarise () groups key data into a single row

summary(flights)

      year          month             day           dep_time    sched_dep_time
 Min.   :2013   Min.   : 1.000   Min.   : 1.00   Min.   :   1   Min.   : 106  
 1st Qu.:2013   1st Qu.: 4.000   1st Qu.: 8.00   1st Qu.: 907   1st Qu.: 906  
 Median :2013   Median : 7.000   Median :16.00   Median :1401   Median :1359  
 Mean   :2013   Mean   : 6.549   Mean   :15.71   Mean   :1349   Mean   :1344  
 3rd Qu.:2013   3rd Qu.:10.000   3rd Qu.:23.00   3rd Qu.:1744   3rd Qu.:1729  
 Max.   :2013   Max.   :12.000   Max.   :31.00   Max.   :2400   Max.   :2359  
                                                 NA's   :8255                 
   dep_delay          arr_time    sched_arr_time   arr_delay       
 Min.   : -43.00   Min.   :   1   Min.   :   1   Min.   : -86.000  
 1st Qu.:  -5.00   1st Qu.:1104   1st Qu.:1124   1st Qu.: -17.000  
 Median :  -2.00   Median :1535   Median :1556   Median :  -5.000  
 Mean   :  12.64   Mean   :1502   Mean   :1536   Mean   :   6.895  
 3rd Qu.:  11.00   3rd Qu.:1940   3rd Qu.:1945   3rd Qu.:  14.000  
 Max.   :1301.00   Max.   :2400   Max.   :2359   Max.   :1272.000  
 NA's   :8255      NA's   :8713                  NA's   :9430      
   carrier              flight       tailnum             origin         
 Length:336776      Min.   :   1   Length:336776      Length:336776     
 Class :character   1st Qu.: 553   Class :character   Class :character  
 Mode  :character   Median :1496   Mode  :character   Mode  :character  
                    Mean   :1972                                        
                    3rd Qu.:3465                                        
                    Max.   :8500                                        
                                                                        
     dest              air_time        distance         hour      
 Length:336776      Min.   : 20.0   Min.   :  17   Min.   : 1.00  
 Class :character   1st Qu.: 82.0   1st Qu.: 502   1st Qu.: 9.00  
 Mode  :character   Median :129.0   Median : 872   Median :13.00  
                    Mean   :150.7   Mean   :1040   Mean   :13.18  
                    3rd Qu.:192.0   3rd Qu.:1389   3rd Qu.:17.00  
                    Max.   :695.0   Max.   :4983   Max.   :23.00  
                    NA's   :9430                                  
     minute        time_hour                  
 Min.   : 0.00   Min.   :2013-01-01 05:00:00  
 1st Qu.: 8.00   1st Qu.:2013-04-04 13:00:00  
 Median :29.00   Median :2013-07-03 10:00:00  
 Mean   :26.23   Mean   :2013-07-03 05:22:54  
 3rd Qu.:44.00   3rd Qu.:2013-10-01 07:00:00  
 Max.   :59.00   Max.   :2013-12-31 23:00:00